Researchers developed a new computational approach designed to better account for changes in gene expression within tumors relative to their unique microenvironments. This approach outperformed current methods for predicting chemotherapy response in patients with triple-negative breast cancer (TNBC).
The new tool, developed by Wenyi Wang, Ph.D., professor of Bioinformatics and Computational Biology, and colleagues, aims to improve upon similar methods to predict treatment responses using an approach known as deconvolution, which involves breaking down, calculating and interpreting cellular differences. This approach also revealed novel insights into population-level characteristics of TNBC.
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